Triple

T2286381
Position Surface form Disambiguated ID Type / Status
Subject Tigray Region E51399 entity
Predicate containsTown P847 FINISHED
Object Hawzen
Hawzen is a town in northern Ethiopia’s Tigray Region, known for its nearby rock-hewn churches and its role in the region’s modern conflicts.
 E252975 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hawzen | Statement: [Tigray Region, containsTown, Hawzen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hawzen
Context triple: [Tigray Region, containsTown, Hawzen]
  • A. Maahas
    Maahas is a barangay (village-level administrative division) within the municipality of Los Baños in the province of Laguna, Philippines.
  • B. Heden
    Heden is a central district in Gothenburg, Sweden, known for its sports facilities, event venues, and open recreational spaces.
  • C. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • D. Havah
    Havah is a transliteration of the Hebrew name for Eve, the first woman in the biblical creation narrative.
  • E. Hauke
    Hauke is a Germanic given name, particularly common in Northern Germany, that is cognate with the English name Hugh.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hawzen
Triple: [Tigray Region, containsTown, Hawzen]
Generated description
Hawzen is a town in northern Ethiopia’s Tigray Region, known for its nearby rock-hewn churches and its role in the region’s modern conflicts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hawzen
Target entity description: Hawzen is a town in northern Ethiopia’s Tigray Region, known for its nearby rock-hewn churches and its role in the region’s modern conflicts.
  • A. Maahas
    Maahas is a barangay (village-level administrative division) within the municipality of Los Baños in the province of Laguna, Philippines.
  • B. Heden
    Heden is a central district in Gothenburg, Sweden, known for its sports facilities, event venues, and open recreational spaces.
  • C. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • D. Havah
    Havah is a transliteration of the Hebrew name for Eve, the first woman in the biblical creation narrative.
  • E. Hauke
    Hauke is a Germanic given name, particularly common in Northern Germany, that is cognate with the English name Hugh.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc24730208190af8a5cf443d334f7 completed March 7, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f1b2a7c8190aa836f9feba2ce1a completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae8004fb6c81908f9fb1678f608419 completed March 9, 2026, 8:08 a.m.
NED2 Entity disambiguation (via description) batch_69ae809ebfdc8190ae404d5711a58b59 completed March 9, 2026, 8:11 a.m.
Created at: March 4, 2026, 7:48 p.m.